protein networks / protein complexes

13. Lecture WS 2003/04

Bioinformatics III 1

Protein Networks / Protein ComplexesProtein networks could be defined in a number of ways

- Co-regulated expression of genes/proteins

- Proteins participating in the same metabolic pathways

- Proteins sharing substrates

- Proteins that are co-localized

- Proteins that form permanent supracomplexes = protein machineries

- Proteins that bind eachother transiently (signal transduction, bioenergetics ... )



A biological cell: a large construction site?

Job office publishes lists (DNA) of people looking for jobs (protein). Managers from the personnel office (DNA-transcription factors) recruit (express) proteins.

Workers (proteins) need to get to their working places (localization).During work they get energy from drinking beer (ATP).

In a biological cell there are many tasks that need to be executed in a timely and precise manner.

All steps depend on interaction of proteins with DNA or with other proteins!



1 Protein-Protein Complexes

It has been realized for quite some time that cells don‘t work by random diffusion of proteins,but require a delicate structural organization into large protein complexes.



Examples of Stable Protein Complexes: Ribosome

The ribosome is a complex subcellular particle composed of protein and RNA. It is the site of protein synthesis,

http://www.millerandlevine.com/chapter/12/cryo-em.html

Model of a ribosome with a newly manufactured protein (multicolored beads) exiting on the right.



Examples of Stable Protein Complexes: ProteasomeThe proteasome is the central enzyme of non-lysosomal protein degradation. It is involved in the degradation of misfolded proteins as well as in the degradation and processing of short lived regulatory proteins.The 20S Proteasome degrades completely unfoleded proteins into peptides with a narrow length distribution of 7 to 13 amino acids.

http://www.biochem.mpg.de/xray/projects/hubome/images/rpr.gifLöwe, J., Stock, D., Jap, B., Zwickl, P., Baumeister, W. and Huber, R. (1995). Crystal structure of the 20S proteasome from the archaeon T. acidophilum at 3.4 Å resolution. Science 268, 533-539.

http://www.biochem.mpg.de/xray/projects/hubome/images/rpr.gif

http://www.biochem.mpg.de/xray/projects/hubome/images/rpr.gif



Stable Protein Complex: Nuclear Pore ComplexA three-dimensional image of the nuclear pore complex (NPC), revealed by electron microscopy. A-B The NPC in yeast. Figure A shows the NPC seen from the cytoplasm while figure B displays a side view.

C-D The NPC in vertebrate (Xenopus).

http://www.nobel.se/medicine/educational/dna/a/transport/ncp_em1.htmlThree-Dimensional Architecture of the Isolated Yeast Nuclear Pore Complex: Functional and Evolutionary Implications, Qing Yang, Michael P. Rout and Christopher W. Akey. Molecular Cell, 1:223-234, 1998

http://www.nobel.se/medicine/educational/dna/a/transport/ncp_em1.html

http://www.nobel.se/medicine/educational/dna/a/transport/ncp_em1.html



Stable Protein Complex: Photosynthetic Unit

Structure suggested byforce field basedmolecular docking.

http://www.ks.uiuc.edu/Research/vmd/gallery

Other large complexes:

- Apoptosome-Thermosome- Transcriptome

Other large complexes:- Apoptosome 7-fold symmetry- Chaperone (GroEL/GroES)

7-fold symmetry- Thermosome- Transcriptome



2 Protein-protein networks



2. Yeast 2-Hybrid Screen

Data on protein-protein interactions fromYeast 2-Hybrid Screen.

One role of bioinformatics is tosort the data.



Protein cluster in yeast

Schwikowski, Uetz, Fields, Nature Biotech. 18, 1257 (2001)

Cluster-algorithm generates one largecluster for proteins interacting with eachother based on binding data of yeast proteins.



Annotation of function


After functional annotation:connect clusters ofinteracting proteins.



Annotation of localization




• study analyzed protein-protein interaction network in yeast S. cerevisae

Yeast two-hybrid screen data identified

2240 direct physical interactions

between 1870 proteins, see

Uetz et al. (1999) und Xenarios et al. (2000).

• analyze the effects of single gene deletions for lethality:

in proteom data base existed 1572 entries of known phenotypic profiles.

Relation between lethality and function as centers in protein networks

Jeong, Mason, Barabási, Oltvai, Nature 411, 41 (2001)



Cluster analysis of 2YHB data.

Shown is largest cluster containing 78% of all proteins.

The color of each node marks the phenotypic effect if this protein is removed from the cell (gene knockout).

red - lethal

green – no effect

orange – slow growth

gelb - unknown

Protein-Protein interactions in yeast





Likehood p(k) of finding proteins in yeast that interact with exactly k other proteins.

Probability has power law dependence.

(Similar plot for bacterium Heliobacter pylori.)

network of protein-protein interactions is a very inhomogenous scale-free network where a few, highly connected, proteins play central roles of mediating the interactions among other, less strongly connected, proteins.





Computational analysis of the tolerance of protein networks for random errors (gene deletions).

Random mutations don’t have an effect on the total topology of the network.

When “hub” proteins with many interactions are eliminated, the diameter of the network decreases quickly.

The degree of proteins being essential (gene knock-out is lethal for cell) depends on the connectivity in the yeast protein network.

Strongly connected proteins with central roles in the architecture of the network are 3 times as essential as proteins with few connections.




3 Identification of protein complexes



Systematic identication of large protein complexesYeast 2-Hybrid-method can only identify binary complexes.

Cellzome company: attach additional protein P to particular protein Pi ,P binds to matrix of purification column. yields Pi and proteins Pk bound to Pi .

Gavin et al. Nature 415, 141 (2002)

Identify proteinsby mass spectro-metry (MALDI-TOF).



Analyis of protein complexes in yeast (S. cerevisae)


Identify proteins byscanning yeast proteindatabase for proteincomposed of fragmentsof suitable mass.

Here, the identifiedproteins are listed according to theirlocalization (a).(b) lists the number ofproteins per complex.



Example of particular complex


Check of the method: can the same complex be obtained for differentchoice of attachment point(tag protein attached to different coponents of complex)? Yes (see gel).

Method allows to identify components of complex, not the binding interfaces.

Better for identification of interfaces:Yeast 2-hybrid screen (binary interactions).

3D models of complexes are importantto develop inhibitors.

- theoretical methods (docking) - electron tomography



3. Netzwerk aus Proteinkomplexen


Service function of Bioinformatics: catalog such data and prepare for analysis ...allowing to formulate new models and concepts (biology!).

If results are very important don‘t wait for some biologist to interpret your data. You may want to get the credit yourself.

Modularity = Formation of separated Islands ??



Structural Proteomics

Sali, Glaeser, Earnest, Baumeister, Nature 422, 216 (2003)

Biological cells are not organized by undirected diffusion of the soluble proteins!

Instead many important cellular functions are carried out by stableor transiently formed protein complexes.



known protein structures

Sali et al. Nature 422, 216 (2003)

PDZ Domäne CheA Aquaporin

Ribosom

Large proteins are underrepresented in the PDB data base.Based on the Cellzome results, people estimatethat each protein complex in yeast contains7.5 proteins.



Single particle analysis with EM

(a) Complexes of 44 tripeptidyl-peptidase II molecules on a surface. The pictures in each line show different averaged views of complexes possessing the same orientation image analysis. (b) 3D-rekonstruction of the TPP II-complex at 3.3 nm resolution.Different views. Note the enhanced resolution by combining information of the different views shown in (a).




Information about macromolecular complexes

‚Subunit structure‘ : atomic resolution < 3 Å‘Subunit shape’ : medium resolution > 3 Å‘Subunit contact’: Knowledge about direct spatial contacts between subunits‘Subunit proximity’: subunits don’t need to be in direct contact.

Grey boxes indicate areas with large experimental difficulties.




Hybrid-methods for macromolecular complexes

Structural Bioinformatics(a) Integration of varios protein elements into one large complex.

(b) Partial atomic model of the entire yeast ribosome by fitting atomic models of rRNA and proteins into a low-resolution EM map of the 80S ribosome.




Structure of large complexes: combine EM + X-ray

docking of atomic X-ray structure of tubulin (3.5 Å resolution)into 8Å-EM-structure of microtubuli.




Situs package: Automated low-resolution fitting

Wriggers et al. J. Mol. Biol. 284, 1247 (1998)

Situs was developed for automatic fitting of high-resolution structures from X-ray crystallography into low-resolution maps from electron microscopy.

http://biomachina.orgsee also database for animations of EM data:http://emotion.biomachina.org/

Idea: Create low-resolution image of X-ray structure.Determine center of mass and moments of inertia.Model one protein by a few mass centers.

Use neuronal network to best position nodes (mass points)into EM density map of the molecular complex.Molecular mass represented by nodes should maximally overlap with EM map.

http://biomachina.org/



Discretization of proteins by few mass points




Reconstruction of actin filament using Situs




Situs package: Conformational Dynamics

Chacon et al. Acta Cryst D 59, 1371 (2003)

In the mean time, the Situs developers have also switched to using FFT techniques to match images and real data.



Electron Tomography

a) The electron beam of the EM microscope is scattered by the central object and the scattered electrons are detected on the black plate.By tilting the object in small steps, we collect electrons scattered at different angles.

b) reconstruction in the computer.Back-projection (Fourier method) of the scatter-information at different angles.The superposition generates a three-dimensional tomogrom.




Identification of macromolecular complexes in cryoelectron tomograms of phantom cells

Frangakis et al., PNAS 99, 14153 (2002)

Prepare „phantom cells“ (ca. 400 nm diameter) with well-defined contents:Liposomes filled with thermosomes and 20S proteasomes.

Thermosome: 933 kD, 16 nm diameter, 15 nm height, subunits assemble into toroidal structure with 8-fold symmetry.20S proteasome: 721 kD, 11.5 nm diameter, 15 nm height, subunits assemble into toroidal structure with 7-fold symmetry.

Collect Cryo-EM pictures of phantom cells for a tilt series from -70º until +70º with 1.5º increments.

Aim: identify and map the 2 types of proteins in the phantom cell.This is a problem of matching a template, ideally derived from a high-resolution structure,to an image feature, the target structure.



Detection and idenfication strategy




Search strategy


Adjust pixel size of templates to the pixel size of the EM 3D reconstruction.The gray value of a voxel (volume element) containing ca. 30 atoms is obtained by

summation of the atomic number of all atoms positioned in it.

Possible search strategies:(i) Scan reconstructed volume by using small boxes of the size of the target structure

(real space method)(ii) Paste template into a box of the size of the reconstructed volume (Fourier space

method). This method is much more efficient.



Correlation with Nonlinear Weighting

R

nn

R

nn

R

nnn

rRrxRx

rxRrxCC

1

22

1

22

1


The correlation coefficient CC is a measure of similarity of two features e.g. a signal x (image) and a template r both with the same size R.Expressed in one dimension:

are the mean values of the subimage and the template.The denominators are the variances

rx and

To derive the local-normalized cross correlation function or, equivalently, the correlation coefficients in a defined region R around each voxel k, which belongs to a large volume N (whereby N >> R), nonlinear filtering has to be applied.This filtering is done in the form of nonlinear weighting.



Raw data


Central x-y slices through the 3D reconstructions of ice-embedded phantom cells filled with

(a) 20S proteasomes, (b) thermosomes, (c) and a mixture of both particles.

At low magnification, the macromolecules appear as small dots.



Correlation coefficients


(a) Histogram of the correlation coefficients of the particles found in the proteasome-containing phantom cell scanned with the "correct" proteasome and the "false" thermosome template. Of the 104 detected particles, 100 were identified correctly. The most probable correlation coefficient is 0.21 for the proteasome template and 0.12 for the thermosome template.

(b) Histogram of the correlation coefficients of the particles found in the thermosome-containing phantom cell. Of the 88 detected particles, 77 were identified correctly. The most probable correlation value is 0.21 for the thermosome template and 0.16 for the proteasome template.

Detection in (a) works well, but is somehow problematic in (b) because (correct) thermosome and proteasome are not well separated.



Reconstruction of phantom cell


Volume-rendered representation of a reconstructed ice-embedded phantom cell containing a mixture of thermosomes and 20S proteasomes. After applying the template-matching algorithm, the protein species were identified according to the maximal correlation coefficient. The molecules are represented by their averages; thermosomes are shown in blue, the 20S proteasomes in yellow. The phantom cell contained a 1:1

ratio of both proteins. The algorithm identifies 52% as thermosomes and 48% as 20S proteasomes.



Electron tomography


- Method has very high computational cost.

- Observation: biological cells are not packed so densely as expected, allowing the identification of single proteins and protein complexes

- Problem for real cells: molecular crowding. Potential difficulties to identify spots.

- need to increase spatial resolution of tomograms



Reconstruction of endoplasmatic reticulum

http://science.orf.at/science/news/61666Dept. of Structural Biology, Martinsried

Picture rights shows rough endoplasmatic reticulum (membrane network in eukaryotic cells that generates proteins and new membranes) coated with ribosomes.

The picture is taken from an intact cell.

Membranes are shown in blue, the ribosomes in green-yellow.

http://science.orf.at/science/news/61666



Reconstruction of actin filaments


Shown is the cytoskeleton of Dictyostelium. Apparently, filaments cross and bridge each other at different angles, and are connected to the cell membrane (right picture).Actin filaments are shown in brown. The cell segment left has a size of 815 x 870 x 97 nm3. Middle: single actin filaments connected at different angles.Right: actin filaments (brown) binding to the cell membrane (blue).

Actin filaments are structural proteins – they form filaments which span the entire cell.They stabilize the cellular shape, are required for motion, and are involved in important cellular transport processes (molecular motors like kinesin walk along these filaments).




Science fiction


Reconstruct proteom of real biological cells.

Required steps:

(1) obtain EM maps of isolated (e.g. 6000 yeast) proteins

(2) enhance resolution of tomography

(3) speed up detection algorithm




Summary

Botstein & Risch, Nature Gen. 33, 228 (2003)

The structural characterization of large multi-protein complexes and the resolution of cellular architectures will likely be achieved by a combination of methods in structural biology:-X-ray crystallography and NMR for high-resolution structures of single proteins and pieces of protein complexes- (Cryo) Electron Microscopy to determine medium-resolution structures of entire protein complexes- Stained EM for still pictures at medium-resolution of cellular organells- (Cryo) Electron Tomography to for 3-dimensional reconstructions of biological cells and for identification of the individual components.

Mapping and idenfication steps require heavy computation.Employ protein-protein docking as a help to identify complexes?

protein networks / protein complexes

Documents

proteinprotein complexesit

protein machineries

protein cluster

jobs protein

large protein complexes

site of protein synthesis

substrates proteins

unfoleded proteins